Gene Expression Profiling of Desmoid Tumors by cDNA Microarrays and Correlation with Progression-Free Survival

被引:31
作者
Salas, Sebastien [1 ,2 ]
Brulard, Celine [3 ]
Terrier, Philippe [4 ]
Ranchere-Vince, Dominique [5 ]
Neuville, Agnes [3 ]
Guillou, Louis [6 ]
Lae, Marick [7 ]
Leroux, Agnes [8 ]
Verola, Olivier [9 ]
Jean-Emmanuel, Kurtz [10 ]
Bonvalot, Sylvie [11 ]
Blay, Jean-Yves [12 ]
Le Cesne, Axel [13 ]
Aurias, Alain [3 ]
Coindre, Jean-Michel [3 ,14 ]
Chibon, Frederic [3 ,15 ]
机构
[1] Aix Marseille Univ, CRO2, INSERM, U911, F-13005 Marseille, France
[2] Timone Hosp, APHM, Dept Med, Div Adult Oncol, Marseille, France
[3] Bergonie Inst, Dept Pathol, INSERM, U916, Bordeaux, France
[4] Inst Gustave Roussy, Dept Pathol, Villejuif, France
[5] Ctr Leon Berard, Dept Pathol, F-69373 Lyon, France
[6] Univ Inst Pathol, Lausanne, Switzerland
[7] Inst Curie, Dept Pathol, Paris, France
[8] Ctr Alexis Vautrin, Dept Pathol, Nancy, France
[9] Hop St Louis, Dept Pathol, Paris, France
[10] Univ Hosp, Dept Hematol & Oncol, Strasbourg, France
[11] Inst Gustave Roussy, Dept Surg, Villejuif, France
[12] Ctr Leon Berard, Dept Med, F-69373 Lyon, France
[13] Inst Gustave Roussy, Dept Med, Villejuif, France
[14] Victor Segalen Univ Bordeaux, Bordeaux, France
[15] Bergonie Inst, Translat Res, Bordeaux, France
关键词
STOMATIN-LIKE PROTEIN-2; SQUAMOUS-CELL CARCINOMA; SLP-2; OVEREXPRESSION; ADAPTER PROTEIN; CANCER; TRIP6; FERROCHELATASE; SIGNATURE; MIGRATION; PROMOTES;
D O I
10.1158/1078-0432.CCR-14-2910
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Purpose:<bold> </bold>Because desmoid tumors exhibit an unpredictable clinical course, translational research is crucial to identify the predictive factors of progression in addition to the clinical parameters. The main issue is to detect patients who are at a higher risk of progression. The aim of this work was to identify molecular markers that can predict progression-free survival (PFS). Experimental Design:<bold> </bold>Gene-expression screening was conducted on 115 available independent untreated primary desmoid tumors using cDNA microarray. We established a prognostic gene-expression signature composed of 36 genes. To test robustness, we randomly generated 1,000 36-gene signatures and compared their outcome association to our define 36-genes molecular signature and we calculated positive predictive value (PPV) and negative predictive value (NPV). Results<bold>: </bold>Multivariate analysis showed that our molecular signature had a significant impact on PFS while no clinical factor had any prognostic value. Among the 1,000 random signatures generated, 56.7% were significant and none was more significant than our 36-gene molecular signature. PPV and NPV were high (75.58% and 81.82%, respectively). Finally, the top two genes downregulated in no-recurrence were FECH and STOML2 and the top gene upregulated in no-recurrence was TRIP6. Conclusions:<bold> </bold>By analyzing expression profiles, we have identified a gene-expression signature that is able to predict PFS. This tool may be useful for prospective clinical studies. (C) 2015 AACR.
引用
收藏
页码:4194 / 4200
页数:7
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